آناليز فضايي عوامل مؤثر بر سرطان كولوركتال با استفاده از مدل رگرسيون وزني جغرافيايي در ايران

Spatial Analysis of Factors Affecting Colorectal Cancer Using the Model of Geographical Weight Regression in Iran

اﻟﮕﻮي رﺧﺪاد ﺑﯿﻤﺎريﻫﺎ در ﺟﻤﻌﯿﺖﻫﺎي ﻣﺨﺘﻠﻒ ﻣﺘﻔﺎوت اﺳﺖ. ﺑﺎ ﺗﻮﺟﻪ ﺑﻪ اﯾﻦﮐﻪ ﺳﺎﻣﺎﻧﻪ اﻃﻼﻋـﺎت ﺟﻐﺮاﻓﯿـﺎﯾﯽ ﻣﯽﺗﻮاﻧـﺪ ﺗﺄﺛﯿﺮ ﻣﮑﺎن را ﺑﺮ رﺧﺪاد و ﭼﮕﻮﻧﮕﯽ ﺗﻮزﯾﻊ ﺑﯿﻤﺎري ﺑﺴﻨﺠﺪ، ﻣﻄﺎﻟﻌﻪاي ﺑﻪﻣﻨﻈﻮر آﻧﺎﻟﯿﺰ ﻓﻀﺎﯾﯽ ﺳﺮﻃﺎن ﮐﻮﻟﻮرﮐﺘﺎل و ﺑﺮﺧﯽ ﻋﻮاﻣﻞ ﺧﻄﺮ آن در اﯾﺮان ﺑﺎ اﺳﺘﻔﺎده از ﺳﺎﻣﺎﻧﻪ اﻃﻼﻋﺎت ﺟﻐﺮاﻓﯿﺎﯾﯽ اﻧﺠﺎم ﺷﺪ. روش ﮐﺎر: اﯾﻦ ﻣﻄﺎﻟﻌﻪ ﺗﻮﺻﯿﻔﯽ- ﺗﺤﻠﯿﻠﯽ ﺑﺎ روﯾﮑﺮد آﻧﺎﻟﯿﺰ ﻓﻀﺎﯾﯽ ﺑﻮده اﺳﺖ. دادهﻫﺎي اﯾﻦ ﻣﻄﺎﻟﻌـﻪ ﺷـﺎﻣﻞ»رﺧـﺪاد ﺳـﺮﻃﺎن ﮐﻮﻟﻮرﮐﺘـﺎل« ﺑﻪﻋﻨﻮان ﻣﺘﻐﯿﺮ واﺑﺴﺘﻪ و ﺳﻪ ﻣﺘﻐﯿﺮ »ﻓﻌﺎﻟﯿﺖ ﺟﺴﻤﯽ«، »ﻧﻤﺎﯾﻪ ﺗﻮده ﺑﺪﻧﯽ« و »ﺳﯿﮕﺎر ﮐﺸﯿﺪن« ﺑﻪﻋﻨﻮان ﻣﺘﻐﯿﺮﻫﺎي ﻣﺴﺘﻘﻞ ﺑﻮدﻧﺪ ﮐﻪ ﺗﻮﺳﻂ اداره ﺳﺮﻃﺎن ﻣﺮﮐﺰ ﻣﺪﯾﺮﯾﺖ ﺑﯿﻤﺎريﻫﺎي ﻏﯿﺮ واﮔﯿﺮ وزارت ﺑﻬﺪاﺷﺖ، درﻣﺎن و آﻣﻮزش ﭘﺰﺷﮑﯽ و ﻧﻈﺎم ﻣﺮاﻗﺒﺖ ﻋﻮاﻣﻞ ﺧﻄﺮ ﺑﯿﻤﺎريﻫﺎي ﻏﯿـﺮ واﮔﯿﺮ ﺑﻪ ﺗﻔﮑﯿﮏ اﺳﺘﺎن و ﺟﻨﺲ در ﺳﺎل 1388)آﺧﺮﯾﻦ ﮔﺰارش( ﺛﺒﺖ ﺷﺪه اﺳﺖ. دادهﻫﺎ ﺑﺎ اﺳﺘﻔﺎده از ﻧﺮماﻓﺰار ArcGISﻧﺴﺨﻪ 10,3 و ﻣﺪل آﻣﺎري رﮔﺮﺳﯿﻮن وزﻧﯽ ﺟﻐﺮاﻓﯿﺎﯾﯽ ﻣﻮرد ﺗﺠﺰﯾﻪ و ﺗﺤﻠﯿﻞ ﻗﺮار ﮔﺮﻓﺘﻨﺪ. ﯾﺎﻓﺘﻪﻫﺎ: ارﺗﺒﺎط ﻓﻀﺎﯾﯽ ﺑﯿﻤﺎري ﺑﺎ ﻣﺘﻐﯿﺮﻫﺎي ﻓﻌﺎﻟﯿﺖ ﺑﺪﻧﯽ، ﻧﻤﺎﯾﻪ ﺗﻮده ﺑﺪﻧﯽ و ﺳﯿﮕﺎر ﮐﺸﯿﺪن ﺑﺎ اﺳﺘﻔﺎده از ﻣﺪل رﮔﺮﺳﯿﻮن وزﻧﯽ ﺟﻐﺮاﻓﯿﺎﯾﯽ ﻣﻮرد ﺗﺄﯾﯿﺪ ﻗﺮار ﮔﺮﻓﺖ؛ ﮐﻪ ﺑﺮ اﯾﻦ اﺳﺎس اﺳﺘﺎنﻫﺎي ﺷﻤﺎﻟﯽ و ﻣﺮﮐﺰي ﻧﺴﺒﺖ ﺑﻪ ﺳـﺎﯾﺮ ﻣﻨـﺎﻃﻖ ﮐﺸـﻮر ﺑﯿﺶﺗـﺮﯾﻦ ﺧﻄـﺮ اﺑـﺘﻼ ﺑـﻪ ﺳـﺮﻃﺎن ﮐﻮﻟﻮرﮐﺘﺎل را ﺑﺎ ﺗﻮﺟﻪ ﺑﻪ اﯾﻦ ﻋﻮاﻣﻞ ﺧﻄﺮ داﺷﺘﻨﺪ. ﻧﺘﯿﺠﻪﮔﯿﺮي: آﻧﺎﻟﯿﺰﻫﺎي ﻓﻀﺎﯾﯽ ﺑﻪ ﺧﻮﺑﯽ ﻣﯽﺗﻮاﻧﻨﺪ در ﺷﻨﺎﺳﺎﯾﯽ ﺳﯿﻤﺎي ﺑﯿﻤﺎري و اوﻟﻮﯾﺖﺑﻨﺪي ﻣﮑﺎﻧﯽ ﻋﻮاﻣﻞ ﻣﺆﺛﺮ ﺑﺮ آن ﻣﻔﯿﺪ واﻗﻊ ﺷﻮﻧﺪ و ﺑﺎ ﺑﺮﻧﺎﻣﻪرﯾﺰيﻫﺎي راﻫﺒﺮدي و اﻗﺪامﻫﺎي ﻣﺪاﺧﻠﻪاي ﺑﯿﻤﺎري را ﮐﻨﺘﺮل ﮐﺮد.

The incidence of colorectal cancer has increased significantly in Iran in recent decades. The pattern of occurrence varies in different populations. A study was conducted to perform a spatial analysis of colorectal cancer and some of its risk factors in Iran using GIS. Methods: The data of this descriptive-analytic study included colorectal cancer incidence as a dependent variable and physical activity, Body Mass Index and smoking as independent variables recorded by the Cancer Department, Center for Non-Communicable Diseases Management, the Ministry of Health and Medical Education and the care system for non-communicable disease risk factors according to province and gender in 2009. Data was analyzed using the ArcGIS 10.3 software and spatial correlation analysis, hot spots analysis, and geographic weighted regression model. Results: The spatial relationship between the disease and some of its risk factors was confirmed by the model of geographical weight regression, according to which the northern and central provinces had the highest risk of colorectal cancer compared to other regions of the country. Conclusion: The results of this study showed that spatial analysis could be useful in identifying disease patterns, prioritizing the factors affecting it, and controlling the disease through strategic planning and interventions.